showcased the fundamentals of Natural Language Processing (NLP) by creating an Airline Sentiment Predictor with logistic regression. Using Streamlit, we've developed an interactive web app for users to analyze traveler sentiments on Twitter, offering practical insights into the airline industry's customer satisfaction and service quality.
active 2023-10-22 → 2023-10-23 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 2 days from 2023-10-22 to 2023-10-23. Pushes: 23 total, peak 18 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
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- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| sendrelagulzar | 23 | 23 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.